Expand description
Total Variation (TV) regularized dipole inversion using ADMM
Solves the L1-regularized inverse problem: min_x ||Dx - f||₂² + λ||∇x||₁
using Alternating Direction Method of Multipliers (ADMM).
Reference: Bilgic, B., Fan, A.P., Polimeni, J.R., et al. (2014). “Fast quantitative susceptibility mapping with L1-regularization and automatic parameter selection.” Magnetic Resonance in Medicine, 72(5):1444-1459. https://doi.org/10.1002/mrm.25029
Reference implementation: https://github.com/kamesy/QSM.jl
Structs§
- TvParams
- TV-ADMM algorithm parameters
Functions§
- shrink 🔒
- Soft thresholding (shrinkage) operator for L1 regularization shrink(x, t) = sign(x) * max(|x| - t, 0)
- tv_admm
- TV-ADMM dipole inversion (optimized)
- tv_
admm_ default - TV-ADMM with default parameters
- tv_
admm_ with_ progress - TV-ADMM with progress callback (optimized)